Abstract
In-store technologies continue to proliferate, but to date, research has not examined the acceptance of these technologies from a comprehensive segmentation lens; that is, simultaneously examine demographic, geographic, psychographic, and behavioral traits of customers. To that end, we collected survey data in 2024 from over 1,300 respondents in the United States to measure variables related to these four segmentation approaches and relate these variables to twenty technologies across five categories in customer purchase journey: technologies that help plan shopping trips, enhance shopping experience, reduce friction, find pricing information, and purchase remotely from the store. Using seemingly unrelated regression (SUR) models, we found that psychographic and behavioral segmentation variables are the most helpful in predicting acceptance of in-store technologies. This research emphasizes to retailers that when considering new cutting-edge retail technologies, customers are not how they look or where they live; they are what they think and how they purchase.